5 Important Steps in Developing a Data Strategy

Posted by Trevor Warren, Data Architect

Oct 21, 2020

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Your data plays a starring role in business planning. That’s why your organization needs to understand how it supports your operations and growth. All of that stored information is one of your most important assets and competitive advantages.

This understanding should reach beyond the present moment and also look toward your future data needs. Developing a scalable data strategy is crucial to business success now and down the road.

With that in mind, let’s take a look at what it takes to build a data strategy roadmap that makes the most of this important organizational asset. 

What is a Data Strategy?

Before you build a data strategy, it’s a good idea to cover what exactly one is, what it does and why your organization should have one. You want to be sure to have solid data buy-in across the organization before you launch an enterprise data strategy.

planningA good data strategy provides you with a vision of how you collect, store, manage, use and share your organization’s data. For most organizations, the amount of data undergoing those activities is only increasing, in some cases in torrents of both structured and unstructured data. The amount of data can be overwhelming.

That’s why implementing a strong data strategy is important. A strategy helps you clarify your data’s purpose and helps you build a roadmap for managing it in a way that benefits everyone in the organization.

More often than not, a company’s data framework isn’t business-focused, but it needs to be. An actionable data strategy should promote efficient resource usage and support an organization’s overall strategy. Data should not be siloed away from overall goals and organizational initiatives. It needs to be an overarching, living entity within your organziation.

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Trevor Warren, Data Architect

Trevor has nearly a decade of experience in solving problems for complex computer systems and improving processes. Trevor earned a Master of Science in Data Science. He is also a Google Cloud Certified Professional - Cloud Architect and Data Engineer.

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